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Merge pull request #54 from 2749113159/master
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Fixing some bugs that come up during the v2.2 test run.
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@joerivanleeuwen
joerivanleeuwen authored Sep 3, 2024
2 parents 1d53aa2 + d51db54 commit dcfe8ab
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Showing 3 changed files with 49 additions and 27 deletions.
8 changes: 5 additions & 3 deletions frbpoppy/beam_dists.py
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Original file line number Diff line number Diff line change
Expand Up @@ -37,7 +37,7 @@ def get_beam_props(model, fwhm):
elif model == 'chime-frb':
pixel_scale = 0.05 # Degrees per pixel [deg]
x_range = 2. # Use 2 deg for CHIME main beam East-West range
beam_array = beam_array[:, 800-20*x_range:800+20*x_range]
beam_array = beam_array[:, 800-20*int(x_range):800+20*int(x_range)]
beam_size = 120*2*x_range # [sq deg]
elif model == 'gaussian':
pixel_scale = fwhm / 95 # Degrees per pixel [deg]
Expand Down Expand Up @@ -179,8 +179,10 @@ def int_pro_random(shape=(1, 1), pattern='perfect', fwhm=2, max_offset=None,
#y_offset = ne.evaluate("(ran_y-b_y) * pixel_scale")

offset = go.separation(0, 0, x_offset, y_offset)

return int_pro, offset, x_offset, y_offset
if pattern == 'chime-frb':
return int_pro, offset, x_offset, y_offset
else:
return int_pro, offset

else:
raise ValueError(f'Beam pattern "{pattern}" not recognised')
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31 changes: 19 additions & 12 deletions frbpoppy/number_density.py
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Original file line number Diff line number Diff line change
Expand Up @@ -69,8 +69,9 @@ def __init__(self,
def sloped_dist(self, n_gen=1):
"""Draw from a sloped distribution to create a logNlogS slope."""

rand = rng.random(n_gen, dtype=np.float32)
vol_co = (self.maxi * rand)**(1/self.power) # [Gpc]
vol_co = (self.maxi*np.random.random(n_gen))**(1/self.power)
#rand = rng.random(n_gen, dtype=np.float32)
#vol_co = (self.maxi * rand)**(1/self.power) # [Gpc]
#vol_co = ne.evaluate("(maxi*rand)**(1/power)", global_dict=vars(self)) # [Gpc]
d = self.dt(vol_co=vol_co)
z = d[0]
Expand All @@ -82,8 +83,9 @@ def from_vol_co(self, n_gen=1):
Can be influenced by changing alpha.
"""
rand = rng.random(n_gen, dtype=np.float32)
vol_co = self.vol_co_max * rand # [Gpc]
vol_co = self.vol_co_max*np.random.random(n_gen)
#rand = rng.random(n_gen, dtype=np.float32)
#vol_co = self.vol_co_max * rand # [Gpc]
#vol_co = ne.evaluate("vol_co_max*rand", global_dict=vars(self)) # [Gpc]
d = self.dt(vol_co=vol_co)
z = d[0]
Expand All @@ -98,8 +100,9 @@ def from_sfr(self, n_gen=1):
Follows Madau & Dickinson (2014), eq. 15. For more info see
https://arxiv.org/pdf/1403.0007.pdf
"""
rand = rng.random(n_gen, dtype=np.float32)
sampling = self.cdf_sfr_max * rand # [Gpc]
sampling = np.random.uniform(0., self.cdf_sfr_max, size=n_gen)
#rand = rng.random(n_gen, dtype=np.float32)
#sampling = self.cdf_sfr_max * rand # [Gpc]
#sampling = ne.evaluate("cdf_sfr_max*rand", global_dict=vars(self)) # [Gpc]
d = self.dt(cdf_sfr=sampling)
z = d[0]
Expand All @@ -115,23 +118,26 @@ def from_delayed_sfr(self, n_gen=1):
https://arxiv.org/pdf/1403.0007.pdf
"""

rand = rng.random(n_gen, dtype=np.float32)
#rand = rng.random(n_gen, dtype=np.float32)

d_list = [0.1, 0.5, 1]
delay_time = min(d_list, key=lambda x:abs(x-self.delay_time))
if delay_time != self.delay_time:
print('Generate cosmic population with delay time', delay_time, 'Gyr instead')

if delay_time == 0.1:
sampling = self.cdf_dsfr0d1_max * rand
sampling = np.random.uniform(0., self.cdf_dsfr0d1_max, size=n_gen)
#sampling = self.cdf_dsfr0d1_max * rand
#sampling = ne.evaluate("cdf_dsfr0d1_max*rand", global_dict=vars(self))
d = self.dt(cdf_dsfr0d1=sampling)
elif delay_time == 0.5:
sampling = self.cdf_dsfr0d5_max * rand
sampling = np.random.uniform(0., self.cdf_dsfr0d5_max, size=n_gen)
#sampling = self.cdf_dsfr0d5_max * rand
#sampling = ne.evaluate("cdf_dsfr0d5_max*rand", global_dict=vars(self))
d = self.dt(cdf_dsfr0d5=sampling)
elif delay_time == 1:
sampling = self.cdf_dsfr1_max * rand
sampling = np.random.uniform(0., self.cdf_dsfr1_max, size=n_gen)
#sampling = self.cdf_dsfr1_max * rand
#sampling = ne.evaluate("cdf_dsfr1_max*rand", global_dict=vars(self))
d = self.dt(cdf_dsfr1=sampling)

Expand All @@ -146,8 +152,9 @@ def from_smd(self, n_gen=1):
Follows Madau & Dickinson (2014), eq. 2 & 15. For more info see
https://arxiv.org/pdf/1403.0007.pdf
"""
rand = rng.random(n_gen, dtype=np.float32)
sampling = self.cdf_smd_max * rand
sampling = np.random.uniform(0., self.cdf_smd_max, size=n_gen)
#rand = rng.random(n_gen, dtype=np.float32)
#sampling = self.cdf_smd_max * rand
#sampling = ne.evaluate("cdf_smd_max*rand", global_dict=vars(self))
d = self.dt(cdf_smd=sampling)
z = d[0]
Expand Down
37 changes: 25 additions & 12 deletions frbpoppy/precalc.py
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Original file line number Diff line number Diff line change
Expand Up @@ -54,11 +54,10 @@ def __init__(self, test=False):
def set_file_name(self):
"""Determine filename."""
uni_mods = os.path.join(paths.models(), 'universe/')
#self.file_name = uni_mods + 'dm_mw.db'
self.file_name = uni_mods + 'dm_mw_ne2001_1d.npy'
self.file_name = uni_mods + 'dm_mw_ne2001.npy'
if self.test:
uni_mods = os.path.join(paths.models(), 'universe/')
self.file_name = uni_mods + 'test_dm_mw_ne2001_1d.npy'
self.file_name = uni_mods + 'test_dm_mw_ne2001.npy'

def create_table(self, parallel=True):
"""Create a lookup table for dispersion measure."""
Expand All @@ -74,7 +73,6 @@ def create_table(self, parallel=True):
start = time.time()
for gl in gls:
for gb in gbs:
print(gl, gb)
if gl in DM_MW_Table:
DM_MW_Table[gl].update({gb: go.ne2001_dist_to_dm(dist, gl, gb)})
else:
Expand All @@ -94,8 +92,16 @@ def lookup(self, gal, gab):
"""
# Load dm table
dm_mw_table_1d = np.load(self.file_name, allow_pickle=True)

dm_mw_table = np.load(self.file_name, allow_pickle=True)
dm_mw_table = dict(enumerate(dm_mw_table.flatten()))[0]

coor_index = range(0, 361*181)
dm_mw_table_1d = []
for i in range(-180, 181):
for j in range(-90, 91):
dm_mw_table_1d.append(dm_mw_table[i][j])
#dm_mw_table_1d = dict(zip(coor_index, dm_mw_table_1d))
dm_mw_table_1d = np.stack((np.array(coor_index), np.array(dm_mw_table_1d)), axis=-1)
# Round values
gal = np.round(gal)
gab = np.round(gab)
Expand Down Expand Up @@ -144,11 +150,10 @@ def __init__(self, test=False):
def set_file_name(self):
"""Determine filename."""
uni_mods = os.path.join(paths.models(), 'universe/')
#self.file_name = uni_mods + 'dm_mw.db'
self.file_name = uni_mods + 'dm_mw_ymw16_1d.npy'
self.file_name = uni_mods + 'dm_mw_ymw16.npy'
if self.test:
uni_mods = os.path.join(paths.models(), 'universe/')
self.file_name = uni_mods + 'test_dm_mw_ymw16_1d.npy'
self.file_name = uni_mods + 'test_dm_mw_ymw16.npy'

def create_table(self, parallel=True):
"""Create a lookup table for dispersion measure."""
Expand All @@ -164,7 +169,6 @@ def create_table(self, parallel=True):
start = time.time()
for gl in gls:
for gb in gbs:
print(gl, gb)
if gl in DM_MW_Table:
DM_MW_Table[gl].update({gb: go.ymw16_dist_to_dm(dist, gl, gb)})
else:
Expand All @@ -185,8 +189,17 @@ def lookup(self, gal, gab):
"""
# Load dm table
dm_mw_table_1d = np.load(self.file_name, allow_pickle=True)

dm_mw_table = np.load(self.file_name, allow_pickle=True)
dm_mw_table = dict(enumerate(dm_mw_table.flatten()))[0]

coor_index = range(0, 361*181)
dm_mw_table_1d = []
for i in range(-180, 181):
for j in range(-90, 91):
dm_mw_table_1d.append(dm_mw_table[i][j])
#dm_mw_table_1d = dict(zip(coor_index, dm_mw_table_1d))
dm_mw_table_1d = np.stack((np.array(coor_index), np.array(dm_mw_table_1d)), axis=-1)

gal = np.round(gal)
gab = np.round(gab)
index = (gal - (-180))*181 + (gab - (-90))
Expand Down

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